| Autor: |
Changye Yang, Sriram Baireddy, Valérian Méline, Enyu Cai, Denise Caldwell, Anjali S. Iyer-Pascuzzi, Edward J. Delp |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
Plant Methods, Vol 19, Iss 1, Pp 1-16 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
1746-4811 |
| DOI: |
10.1186/s13007-023-01026-w |
| Popis: |
Abstract Background Environmental stress due to climate or pathogens is a major threat to modern agriculture. Plant genetic resistance to these stresses is one way to develop more resilient crops, but accurately quantifying plant phenotypic responses can be challenging. Here we develop and test a set of metrics to quantify plant wilting, which can occur in response to abiotic stress such as heat or drought, or in response to biotic stress caused by pathogenic microbes. These metrics can be useful in genomic studies to identify genes and genomic regions underlying plant resistance to a given stress. Results We use two datasets: one of tomatoes inoculated with Ralstonia solanacearum, a soilborne pathogen that causes bacterial wilt disease, and another of soybeans exposed to water stress. For both tomato and soybean, the metrics predict the visual wilting score provided by human experts. Specific to the tomato dataset, we demonstrate that our metrics can capture the genetic difference of bacterium wilt resistance among resistant and susceptible tomato genotypes. In soybean, we show that our metrics can capture the effect of water stress. Conclusion Our proposed RGB image-based wilting metrics can be useful for identifying plant wilting caused by diverse stresses in different plant species. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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